“Probability Universe” Introductory Series · Issue 02
A Cruel Fact
You’ve surely heard stories like this:
A successful person, who had nothing when young, through hard work and persistence, eventually became an industry leader. In speeches, they say: “As long as you work hard enough, you will definitely succeed.”
Thunderous applause from the audience.
But no one asks: What about those who worked just as hard, or even harder, but failed?
They’re not on stage. They won’t be interviewed. Their stories won’t be written into books.
This is survivorship bias.
The “hard work → success” causal chain you see has been filtered. Those “hard work → failure” cases have been systematically screened out.
The Expected Value Trap
Let’s do a simple math problem.
Suppose there’s an investment opportunity:
- 90% probability of earning 1 million
- 10% probability of losing 10 million
Expected value = 0.9 × 1 million + 0.1 × (-10 million) = 0.9 - 1 = -0.1 million
From an expected value perspective, this is a losing game. But if you only look at the “success cases,” you’ll see a group of people who made 1 million, telling you: “This opportunity is amazing!”
What about those who lost 10 million? They went bankrupt, disappeared, and won’t appear in your field of vision.
The logic of “hard work leads to success” is essentially the life version of this trap.
Non-ergodicity: Time Paths Cannot Be Repeated
Here we introduce a key concept: Non-ergodicity.
What is ergodicity?
Imagine you’re playing roulette at a casino. If you play infinitely many times, your average return will approach “the average return of everyone playing once.” This is ergodicity—time average equals ensemble average.
But life isn’t like this.
You only have one life. You can’t “start over.” You can’t “average.”
Even if a strategy is correct in the “ensemble average” sense, for you as a single-path individual, it could be a one-time annihilation.
A Thought Experiment
Suppose 100 people each have 1 million in capital, participating in a game:
- Each round: 50% probability of doubling, 50% probability of going to zero
- Play 10 rounds
From an ensemble average perspective:
- After round 1: 50 people have 2 million, 50 people have zero
- After round 2: 25 people have 4 million, 75 people have zero
- ……
- After round 10: About 0.1 people have 1 billion, 99.9 people have zero
Expected value: Each person’s expected wealth = 1 million × (1.5)^10 ≈ 57 million
Looks great! On average, each person could earn 57 million!
But the reality is: 99.9% of people end up with zero.
That “average 57 million” figure is pulled up by the 0.1% super-winners. For 99.9% of people, the result of this game is: nothing at all.
Why “Hard Work Leads to Success” Is a Lie
Now you understand:
- Survivorship Bias: You only see the successful, not the failed
- Expected Value Trap: Ensemble average doesn’t equal individual outcome
- Non-ergodicity: You only have one life; you can’t “average”
Combining these three points:
“Hard work leads to success” is toxic chicken soup fed to you by survivors in a non-ergodic world, using expected value thinking.
It’s not completely wrong—hard work does increase the probability of success. But it hides a fatal premise: You must survive to play until the end.
If you go to zero in round three, the subsequent probabilities are meaningless to you.
The Correct Way of Thinking
So, in a non-ergodic world, what’s the correct way of thinking?
Not pursuing “expected value maximization,” but pursuing “living long.”
Specifically:
- Manage the Left Tail First, Then Pursue the Right Tail
The “left tail” is the worst-case region of the probability distribution. Before pursuing “making big money,” first ensure “not dying.”
- Don’t Treat High Probability as a Promise
A 90% success rate means a 10% failure rate. If that 10% would knock you out, the 90% is meaningless to you.
- Maintain Optionality
Don’t bet all your chips on one outcome. Preserve the right to retreat, preserve the ability to pivot.
- Distinguish “Repeatable” from “Non-repeatable”
If something can be done 100 times repeatedly, you can use expected value thinking. If something can only be done once, you must use survival thinking.
A More Honest Statement
If we were to rewrite “hard work leads to success” into a more honest version, it should be:
“Working hard in the right structure, while ensuring failure won’t knock you out, will significantly increase your probability of success over the long term.”
Not inspiring enough?
But this is the truth.
Summary
- “Hard work leads to success” is a product of survivorship bias + expected value trap + ergodicity assumption
- Life is non-ergodic: You only have one chance; you can’t “average”
- Correct thinking: First ensure you don’t die, then pursue success
- It’s not about not working hard, but working hard in the right structure while managing left-tail risk
Boundary Statement
This article isn’t saying “hard work is useless.”
Hard work is certainly useful. But the function of hard work is “increasing probability,” not “guaranteeing results.”
More importantly: The direction and structure of effort matter more than the intensity of effort.
Working desperately hard in the wrong structure is worse than working moderately hard in the right structure.
This is what we’ll discuss next: Ridgelines—the “highways” in the probability cloud.
Next Issue Preview: The Highway of Fate—Ridgelines
This article is based on the SPUD theoretical framework (Structure-Probability Unified Dynamics) Series articles continuously updated
原文：https://x.com/unicome163/status/2019661982337482904